943 resultados para Letters of credit.
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Introduction of agrarian reforms and introduction of new technology increased dependence on casual labourers. High labour absorption in the subsistence agriculture and increased price of input resulted in high cost of cultivation. Price of paddy did not rise correspondingly. As a result subsistence economy's future is bleak. The purpose of the _study is to examine these arguments and related issues with the help of empirical evidence from Kuttanad. The credit schemes are designed to help farmers to earn higher incomes by larger output brought either by an increase in area or by an improvement in yield rates or both. It is difficult to isolate the impact of agricultural credit on agricultural development. Because agricultural development is the combined effect of all inputs. The specific .criteria selected for analysing the impact of agricultural icredit are how increased supply of credit would bring changes ‘in capital formation, agrarian relations, informal lending and its cost and the changes in area, output, introduction of new technology, income, savings and employment of farm households.
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This paper uses the data of 1338 rural households in the Northern Mountainous Region of Vietnam to examine the extent to which subsidised credit targets the poor and its impacts. Principal Component Analysis and Propensity Score Matching were used to evaluate the depth of outreach and the income impact of credit. To address the problem of model uncertainty, the approach of Bayesian Model Average applied to the probit model was used. Results showed that subsidised credit successfully targeted the poor households with 24.10% and 69.20% of clients falling into the poorest group and the three bottom groups respectively. Moreover, those who received subsidised credit make up 83% of ethnic minority households. These results indicate that governmental subsidies are necessary to reach the poor and low income households, who need capital but are normally bypassed by commercial banks. Analyses also showed that ethnicity and age of household heads, number of helpers, savings, as well as how affected households are by shocks were all factors that further explained the probability at which subsidised credit has been assessed. Furthermore, recipients obtained a 2.61% higher total income and a 5.93% higher farm income compared to non-recipients. However, these small magnitudes of effects are statistically insignificant at a 5% level. Although the subsidised credit is insufficient to significantly improve the income of the poor households, it possibly prevents these households of becoming even poorer.
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This paper investigates the role of credit and liquidity factors in explaining corporate CDS price changes during normal and crisis periods. We find that liquidity risk is more important than firm-specific credit risk regardless of market conditions. Moreover, in the period prior to the recent “Great Recession” credit risk plays no role in explaining CDS price changes. The dominance of liquidity effects casts serious doubts on the relevance of CDS price changes as an indicator of default risk dynamics. Our results show how multiple liquidity factors including firm specific and aggregate liquidity proxies as well as an asymmetric information measure are critical determinants of CDS price variations. In particular, the impact of informed traders on the CDS price increases when markets are characterised by higher uncertainty, which supports concerns of insider trading during the crisis.
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This paper traces the developments of credit risk modeling in the past 10 years. Our work can be divided into two parts: selecting articles and summarizing results. On the one hand, by constructing an ordered logit model on historical Journal of Economic Literature (JEL) codes of articles about credit risk modeling, we sort out articles which are the most related to our topic. The result indicates that the JEL codes have become the standard to classify researches in credit risk modeling. On the other hand, comparing with the classical review Altman and Saunders(1998), we observe some important changes of research methods of credit risk. The main finding is that current focuses on credit risk modeling have moved from static individual-level models to dynamic portfolio models.
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Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.
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Credit markets with asymmetric information often prefer credit rationing as a profit maximizing device. This paper asks whether the presence of informal credit markets reduces the cost of credit rationing, that is, whether it can alleviate the impact of asymmetric information based on the available information. We used a dynamic general equilibrium model with heterogenous agents to assess this. Using Indian credit market data our study shows that the presence of informal credit market can reduce the cost of credit rationing by separating high risk firms from the low risk firms in the informal market. But even after this improvement, the steady state capital accumulation is still much lower as compared to incentive based market clearing rates. Through self revelation of each firm's type, based on the incentive mechanism, banks can diversify their risk by achieving a separating equilibrium in the loan market. The incentive mechanism helps banks to increase capital accumulation in the long run by charging lower rates and lending relatively higher amount to the less risky firms. Another important finding of this study is that self-revelation leads to very significant welfare improvement, as measured by consumptiuon equivalence.
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This paper examines whether the presence of informal credit markets reduces the cost of credit rationing in terms of growth. In a dynamic general equilibrium framework, we assume that firms are heterogenous with different degrees of risk and households invest in human capital development. With the help of Indian household level data we show that the informal market reduces the cost of rationing by increasing the growth rate by 0.7 percent. This higher growth rate, in the presence of an informal sector, is due to the ability of the informal market to separate the high risk from the low risk firms thanks to better information. But even after such improvement we do not get the optimum outcome. The findings, based on our second question, suggest that the revelation of firms' type, based on incentive compatible pricing, can lead to almost 2 percent higher growth rate as compared to the credit rationing regime with informal sector.
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This paper describes and compares the institutional framework of the agricultural credit markets in selected European countries. The institutions can be both formal (rules, regulations, authorities and actors) and informal (norms, values and relations). They also interact and in situations where the formal institutions are weak, the informal ones increase in importance. The study is based on a questionnaire sent to agricultural financial experts in selected countries. The case studies show that credit regulations are typically general, with no specific regulations for the agricultural credit market. On the other hand, several countries support agricultural credit in various forms, implying that the governments do not perceive the general credit market to function in the case of agricultural firms. In a risk assessment, the most frequent reasons for rejecting a loan application are all linked to economic performance and the situation of the farmer. Personal characteristics, such as educational level or lack of experience, were generally perceived as less influential. Another interesting point when it comes to risk assessment is that in some countries the importance of asset-based lending compared with cash flow-based lending seems to differ when concerning a first-time applicant and when there is an application to extend a loan. To get an idea of the availability of credit, the loan-to-value (LTV) ratio was calculated, and it showed remarkably low values for Poland and Slovakia. For all the countries, the calculated value was lower than what the financial experts would have expected. This might imply credit rationing in agriculture in some of the countries studied. The financial experts all judged the possibility of an agricultural firm obtaining a loan as higher than that for other small rural firms, implying that the latter are also credit-rationed.
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The author ascribes the letters of Junius to John Horne, afterwards John Horne Tooke.
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First published in this edition 1838.
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Presented to the Roxburghe club by Arthur James Balfour.
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Includes bibliographical references.
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Life and letters of Fredk. W. Robertson edited by Stopford A. Brooke.
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Bound with: James Hough. A reply to the letters of the Abbé Dubois on the state of Christianity in India. London, Seeley & Son, 1824.
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The letters of Cicero and Pliny translated by William Melmoth (p. 1-80)